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Volumn , Issue , 2011, Pages

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Author keywords

automatic tuning; code generation; CUDA; GPGPU; OpenCL; sparse linear algebra; SpMV

Indexed keywords

AUTOMATIC TUNING; CODE GENERATION; CUDA; GPGPU; OPENCL; SPARSE LINEAR ALGEBRA; SPMV;

EID: 79955053359     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1964179.1964196     Document Type: Conference Paper
Times cited : (6)

References (8)
  • 1
    • 74049143158 scopus 로고    scopus 로고
    • Implementing sparse matrix-vector multiplication on throughput-oriented processors
    • Nathan Bell and Michael Garland. Implementing sparse matrix-vector multiplication on throughput-oriented processors. In SC, 2009.
    • (2009) SC
    • Bell, N.1    Garland, M.2
  • 2
    • 77749340082 scopus 로고    scopus 로고
    • Model-driven autotuning of sparse matrix-vector multiply on GPUs
    • Jee W. Choi, Amik Singh, and Richard W. Vuduc. Model-driven autotuning of sparse matrix-vector multiply on GPUs. In PPoPP, 2010.
    • (2010) PPoPP
    • Choi, J.W.1    Singh, A.2    Vuduc, R.W.3
  • 3
    • 73349098372 scopus 로고
    • Technical Report CNA-150, Center for Numerical Analysis, University of Texas, Austin, Texas
    • David R. Kincaid, John R. Respess, and David M. Young. ITPACK 2.0 user's guide. Technical Report CNA-150, Center for Numerical Analysis, University of Texas, Austin, Texas, 1979.
    • (1979) ITPACK 2.0 User's Guide
    • Kincaid, D.R.1    Respess, J.R.2    Young, D.M.3
  • 4
    • 0033691759 scopus 로고    scopus 로고
    • Next-generation generic programming and its application to sparse matrix computations
    • Nikolay Mateev, Keshav Pingali, Paul Stodghill, and Vladimir Kotlyar. Next-generation generic programming and its application to sparse matrix computations. In ICS, 2000.
    • (2000) ICS
    • Mateev, N.1    Pingali, K.2    Stodghill, P.3    Kotlyar, V.4
  • 5
    • 79955066714 scopus 로고    scopus 로고
    • Automatically tuning sparse matrix-vector multiplication for GPU architectures
    • Alexander Monakov, Anton Lokhmotov, and Arutyun Avetisyan. Automatically tuning sparse matrix-vector multiplication for GPU architectures. In HiPEAC, 2010.
    • (2010) HiPEAC
    • Monakov, A.1    Lokhmotov, A.2    Avetisyan, A.3
  • 6
    • 79959466764 scopus 로고    scopus 로고
    • Optimization principles and application performance evaluation of a multithreaded GPU using CUDA
    • Shane Ryoo, Christopher I. Rodrigues, Sara S. Baghsorkhi, Sam S. Stone, David B. Kirk, and Wen-mei W. Hwu. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA. In PPoPP, 2008.
    • (2008) PPoPP
    • Ryoo, S.1    Rodrigues, C.I.2    Baghsorkhi, S.S.3    Stone, S.S.4    Kirk, D.B.5    Hwu, W.W.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.